Walton
et al. (2011) applied dimensional, categorical, and hybrid
models to analyses of CBCL and YSR scores obtained by an epidemiological
sample of 2,027 Dutch youths at ages 11.1 and 13.6 years.
For dimensional analyses, a latent trait model described the
probability that each particular problem item would be endorsed
on the basis of the youth's level on a continuous latent trait.
For categorical analyses, a latent class model categorized
youths into discrete classes according to patterns of item
scores. And for the hybrid analyses, a factor mixture model
categorized youths into discrete classes but allowed for heterogeneity
within each class with respect to the severity of scores.
For both the Aggressive Behavior and Rule-Breaking Behavior
syndromes, the latent trait model fit the data better than
the latent class and hybrid models at ages 11.1 and 13.6,
for both boys and girls. Walton et al. concluded "that
classification models can be based on empirical evidence rather
than a priori preferences, and while current classification
systems conceptualize externalizing problems in terms of discrete
groups, they can be better conceptualized as dimensions"
(p. 553).